Important reservoir properties such as porosity or permeability controlling reservoir storativity and productivity are critically influenced by pore space characteristics, which cannot be reduced on a purely volumetric effect. Pore size, pore shape and interface effects exert the strongest influence and the relationships between these properties are not well understood yet. Pore space properties are especially complex in carbonate rocks, where diverse pore types and pore geometries, as well as complicated pore structures (different scales, shapes and connectivities) exist. In this study, experimental investigations combining different measurement techniques and results of model calculations for carbonate reservoir rocks were used to achieve a better understanding of parameters controlling electrical and hydraulic conductivity (permeability). A modified Archie relationship for water-saturated carbonate rocks has been developed, considering electrically relevant pore types (interparticle, fracture and connected vug porosity; i.e. effective porosity) and separate vugs, which contribute only marginally to electrical conductivity. Central to this concept is the application of two Archie exponents: Exponent m related to connected porosity and exponent m* related to total porosity. Regressions for calculation of exponent m and effective porosity from total porosity and resistivity data have been established for a partitioning of total porosity derived from porosity logs into interparticle, fracture and separate vug porosity. New capillary type pore models have been developed for interparticle porosity covering curved and cone-shaped pore geometries. They numerically explain the influence of pore body and pore throat radius on all considered properties (porosity, specific surface, permeability, electrical resistivity) for “non-cylindrical” pore channels. Model equations deliver three essential results: (1) The mostly empirically formulated influences of pore shape on the petrophysical properties investigated could be covered by the models and their effect on these parameters could be calculated. (2) Using this information, empirically derived parameters (RQI, FZI) can be explained by the models. (3) The identified influencing factors (pore size, ratio of pore body to pore throat radius, tortuosity, porosity) are covered separately in the equations representing the parameters investigated, which allows an individual analysis.